2017 Network Control Systems

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Academic unit or major
Graduate major in Systems and Control Engineering
Instructor(s)
Hayakawa Tomohisa  Hatanaka Takeshi 
Course component(s)
Lecture     
Day/Period(Room No.)
Fri3-4(S511)  
Group
-
Course number
SCE.C533
Credits
1
Academic year
2017
Offered quarter
4Q
Syllabus updated
2017/4/26
Lecture notes updated
-
Language used
English
Access Index

Course description and aims

From the 2000s, a number of research works have been devoted to control of networked systems, in particular, control of multi-agent systems wherein the goal is to present inter-agent local interaction laws leading to desirable global behavior. Currently, it is not too much to say that knowledge on this theory is indispensable for doing advanced research. The network control systems include applications such as sensor networks, smart energy management systems, intelligent transportation systems and system biology, which are all relevant to the present social issues. This course starts with introduction to graph theory which was newly brought to control engineering by control of network systems. Students then learn the most fundamental control problem of multi-agent systems, namely, consensus control. Moreover, this course also addresses advanced issues such as synchronization control, coverage control and cooperative distributed optimization.

Student learning outcomes

This course treats network control systems and educates the concept, problem formulations, solutions and background theory. Through this course, students would know several typical control problems, applications and fundamental theory of network control systems. This would help students have access to the state-of-the-art in systems and control, and to produce novel research outcomes. Also, students will acquire several background theories such as graph theory, Lyapunov theory and optimization theory.

Keywords

Network Control Systems, Multi-agent Systems, Graph Theory, Consensus Control, Synchronization Control, Coverage Control, Cooperative Distributed Optimmization

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

1) At the beginning of each class, solutions to exercise problems assigned in the previous class are reviewed.
2) Attendance is taken in every class.
3) Students must familiarize the contents assigned in the previous class before coming to the class.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Network Control Systems Students must make sure they understand what significance the course holds for them by checking their learning portfolio. Peruse Chapter 1 of the course textbook
Class 2 Graph Theory Peruse Chapter 2 of the course textbook
Class 3 Continuous-Time Consensus Control Peruse Section 3.1 and 3.2 of the course textbook. The homework must be handed in next class.
Class 4 Discrete-Time Consensus Control Peruse Section 3.3 and 3.4 of the course textbook The homework must be handed in next class.
Class 5 Synchronization Control The homework must be handed in next class.
Class 6 Coverage Control Peruse Chapter 4 of the course textbook. The homework must be handed in next class.
Class 7 Cooperative Distributed Optimization Peruse Chapter 5 of the course textbook The homework must be handed in next class.
Class 8 Course Summary

Textbook(s)

M. Mesbahi and M. Egerstedt, Graph Theoretic Methods in Multiagent Networks,
Princeton Series in Applied Mathematics, Princeton University Press ISBN: 9781400835355

Reference books, course materials, etc.

S. Azuma and M. Nagahara (eds.), Control of Multi-agent Systems ISBN: 9784339033229

Assessment criteria and methods

Students will be assessed on their understanding of the concept of network control systems, theory, solution and their applications. The course scores are based on exercise problems.

Related courses

  • SCE.C202 : Feedback Control
  • SCE.C301 : Linear System Theory
  • SCE.C402 : Robust Control
  • SCE.C531 : Nonlinear and Adaptive Control
  • SCE.C501 : Optimal Control
  • SCE.C502 : Hybrid Systems Control

Prerequisites (i.e., required knowledge, skills, courses, etc.)

Students must have successfully completed SCE.C.202, SCE.C.302, SCE.C.402, SCE.C.531, SCE.C.501, and SCE.C.502 or have equivalent knowledge.

Contact information (e-mail and phone)    Notice : Please replace from "[at]" to "@"(half-width character).

Hayakawa: tel 03-5734-2762, email hayakawa[at]mei.titech.ac.jp
Hatanaka: tel 03-5734-3316, email hatanaka[at]ctrl.titech.ac.jp

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